| Autor: |
Arun Kumar, Aziz Nanthaamornphong |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Discover Applied Sciences, Vol 6, Iss 11, Pp 1-13 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
3004-9261 |
| DOI: |
10.1007/s42452-024-06292-4 |
| Popis: |
Abstract Orthogonal Time Frequency Space (OTFS) is regarded as one of the best contenders for sixth-generation (6G) radio systems due to its ability to obtain excellent performance in high-speed scenarios. Peak-to-average power ratio (PAPR) significantly impacts and degrades the efficiency of the power amplifier used in OTFS-based 6G systems. The proposed article presents a genetic hybrid algorithm, Partial transmission sequence-particle swarm optimization (PTS-PSO), obtaining an optimal PAPR performance with low computation complexity. The PSO generates the best phase factor compared to the conventional phase generation method of PTS, making PTS-PSO more effective. The impacts such as PAPR, bit error rate (BER), power spectral density (PSD), and complexity of the proposed PTS-PSO are compared with the conventional selective mapping (SLM) and PTS methods for 64, 256, and 512 OTFS sub-carriers. The projected PTS-PSO attained a PAPR and PSD gain of 1–6 dB and − 540 while preserving the BER performance. The experimental results demonstrate that the projected PTS-PSO outperforms the conventional SLM and PTS algorithms with trivial intricacy. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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